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In the 30 years that I have been carrying out research into addiction, the one question that I have been asked the most – particularly by those who work in the print and broadcast media – is whether there is such a thing as an ‘addictive personality’? In a previous blog I briefly reviewed the concept of ‘addictive personality’ but since publishing that article, I have published a short paper in the Global Journal of Addiction and Rehabilitation Medicine on addictive personality, and in this blog I review I outline some of the arguments as to why I think addictive personality is a complete myth.

Psychologists such as Dr. Thomas Sadava have gone as far to say that ‘addictive personality’ is theoretically necessary, logically defensible, and empirically supportable. Sadava argued that if ‘addictive personality’ did not exist then every individual would vulnerable to addiction if they lived in comparable environments, and that those who were addicted would differ only from others in the specifics of their addiction (e.g., alcohol, nicotine, cocaine, heroin). However, Sadava neglected genetic/biological predispositions and the structural characteristics of the substance or behaviour itself.

There are many possible reasons why people believe in the concept of ‘addictive personality’ including the facts that: (i) vulnerability is not perfectly correlated to one’s environment, (ii) some addicts are addicted to more than one substance/activity (cross addiction) and engage themselves in more than one addictive behaviour, and (iii) on giving up addiction some addicts become addicted to another (what I and others have referred to as ‘reciprocity’). In all the papers I have ever read concerning ‘addictive personality’, I have never read a good operational definition of what ‘addictive personality’ actually is (beyond the implicit assumption that it refers to a personality trait that helps explain why individuals become addicted to substances and/or behaviours). Dr. Craig Nakken in his book The Addictive Personality: Understanding the Addictive Process and Compulsive Behaviour argued that ‘addictive personality’ is “created from the illness of addiction”, and that ‘addictive personality’ is a consequence of addiction and not a predisposing factor. In essence, Nakken simply argued that ‘addictive personality’ refers to the personality of an individual once they are addicted, and as such, this has little utility in understanding how and why individuals become addicted.

When teaching my own students about the concept of ‘addictive personality’ I always tell them that operational definitions of constructs in the addictive behaviours field are critical. Given that I have never seen an explicit definition of ‘addictive personality’ I provide my own definition and argue that ‘addictive personality’ (if it exists) is a cognitive and behavioural style which is both specific and personal that renders an individual vulnerable to acquiring and maintaining one or more addictive behaviours at any one time. I also agree with addiction experts that the relationship between addictive characteristics and personality variables depend on the theoretical considerations of personality. According to Dr. Peter Nathan there must be ‘standards of proof’ to show valid associations between personality and addictive behaviour. He reported that for the personality trait or factor to genuinely exist it must: (i) either precede the initial signs of the disorder or must be a direct and lasting feature of the disorder, (ii) be specific to the disorder rather than antecedent, coincident or consequent to other disorders/behaviours that often accompany addictive behaviour, (iii) be discriminative, and (iv) be related to the addictive behaviour on the basis of independently confirmed empirical, rather than clinical, evidence. As far as I am aware, there is no study that has ever met these four standards of proof, and consequently I would argue on the basis of these that there is no ‘addictive personality’.

Although I do not believe in the concept of ‘addictive personality’ this does not mean that personality factors are not important in the acquisition, development, and maintenance of addictive behaviours. They clearly are. For instance, a paper in the Psychological Bulletin by Dr. Roman Kotov and his colleagues examined the associations between substance use disorders (SUDs) and higher order personality traits (i.e., the ‘big five’ of openness to experience, conscientiousness, agreeableness, extraversion, and neuroticism) in 66 meta-analyses. Their review included 175 studies (with sample sizes ranged from 1,076 to 75,229) and findings demonstrated that SUD addicts were high on neuroticism (and was the strongest personality trait associated with SUD addiction) and low on conscientiousness. Many of the studies the reviewed also reported that agreeableness and openness were largely unrelated to SUDs.

Dr. John Malouff and colleagues carried published a meta-analysis in the Journal of Drug Education examining the relationship between the five-factor model of personality and alcohol. The meta-analysis included 20 studies (n=7,886) and showed alcohol involvement was associated with low conscientiousness, low agreeableness, and high neuroticism. Mixed-sex samples tended to have lower effect sizes than single-sex samples, suggesting that mixing sexes in data analysis may obscure the effects of personality. Dr. James Hittner and Dr. Rhonda Swickert published a meta-analysis in the journal Addictive Behaviors examining the association between sensation seeking and alcohol use. An analysis of 61 studies revealed a small to moderate size heterogeneous effect between alcohol use and total scores on the sensation seeking scale. Further analysis of the sensation seeking components indicated that disinhibition was most strongly correlated with alcohol use.

Dr. Marcus Munafo and colleagues published a meta-analysis in the journal Nicotine and Tobacco Research examining strength and direction of the association between smoking status and personality. They included 25 cross-sectional studies that reported personality data for adult smokers and non-smokers and reported a significant difference between smokers and non-smokers on both extraversion and neuroticism traits. In relation to gambling disorder, Dr. Vance MacLaren and colleagues published a meta-analysis of 44 studies that had examined the personality traits of pathological gamblers (N=2,134) and non-pathological gambling control groups (N=5,321) in the journal Clinical Psychology Review. Gambling addiction was shown to be associated with urgency, premeditation, perseverance, and sensation seeking aspects of impulsivity. They concluded that individual personality characteristics may be important in the aetiology of pathological gambling and that the findings were similar to the meta-analysis of substance use disorders by Kotov and colleagues.

More recently, I co-authored a study with Dr. Cecilie Andreassen and her colleagues in the Journal of Behavioral Addictions. We carried out the first ever study investigating the inter-relationships between the ‘big five’ personality traits and behavioural addictions. They assessed seven behavioural addictions (i.e., Facebook addiction, video game addiction, Internet addiction, exercise addiction, mobile phone addiction, compulsive buying, and study addiction). Of 21 inter-correlations between the seven behavioural addictions, all were positive (and nine significantly so). More specifically: (i) neuroticism was positively associated with Internet addiction, exercise addiction, compulsive buying, and study addiction, (ii) extroversion was positively associated with Facebook addiction, exercise addiction, mobile phone addiction, and compulsive buying, (iii) openness was negatively associated with Facebook addiction and mobile phone addiction, (iv) agreeableness was negatively associated with Internet addiction, exercise addiction, mobile phone addiction, and compulsive buying, and (v) conscientiousness was negatively associated with Facebook addiction, video game addiction, Internet addiction, and compulsive buying and positively associated with exercise addiction and study addiction. However, replication and extension of these findings is needed before any definitive conclusions can be made.

Overall these studies examining personality and addiction consistently demonstrate that addictive behaviours are correlated with high levels of neuroticism and low levels of conscientiousness. However, there is no evidence of a single trait (or set of traits) that is predictive of addiction, and addiction alone. Others have also reached the same conclusion based on the available evidence. For instance, R.G. Pols (in Australian Drug/Alcohol Review) noted that findings from prospective studies are inconsistent with retrospective and cross-sectional studies leading to the conclusion that the ‘addictive personality’ is a myth. Dr. John Kerr in the journal Human Psychopharmacology: Clinical and Experimental noted that ‘addictive personality’ had long been argued as a viable construct (particularly in the USA) but that there is simply no evidence for the existence of a personality type that is prone to addiction. In another review of drug addictions, Kevin Conway and colleagues asserted (in the journal Drug and Alcohol Dependence) there was scant evidence that personality traits were associated with psychoactive substance choice. Most recently, Maia Szalavitz in her book Unbroken Brain: A Revolutionary New Way of Understanding Addiction noted that:

“Fundamentally, the idea of a general addictive personality is a myth. Research finds no universal character traits that are common to all addicted people. Only half have more than one addiction (not including cigarettes)—and many can control their engagement with some addictive substances or activities, but not others”.

Clearly there are common findings across a number of differing addictions (such as similarities in personality profiles using the ‘big five’ traits) but it is hard to establish whether these traits are antecedent to the addiction or caused by it. Within most addictions there appear to be more than one sub-type of addict suggesting different pathways of how and way individuals might develop various addictions. If this is the case – and I believe that it is – where does that leave the ‘addictive personality’ construct?

‘Addictive personality’ is arguably a ‘one type fits all’ approach and there is now much evidence that the causes of addiction are biopsychosocial from an individual perspective, and that situational determinants (e.g., accessibility to the drug/behaviour, advertising and marketing, etc.) and structural determinants (e.g., toxicity of a specific drug, game speed in gambling, etc.) can also be influential in the aetiology of problematic and addictive behaviours. Another problem with ‘addictive personality’ being an explanation for why individuals develop addictions is that the concept inherently absolves an individual’s responsibility of developing an addiction and puts the onus on others in treating the addiction. Ultimately, all addicts have to take some responsibility in the development of their problematic behaviour and they have to take some ownership for overcoming their addiction. Personally, I believe it is better to concentrate research into risk and protective factors of addiction rather than further research of ‘addictive personality’.

As I have argued in a number of my papers and book chapters, not every addict has a personality disorder, and not every person with a personality disorder has an addiction. While some personality disorders appear to have an association with addiction including Antisocial Personality Disorder and Borderline Personality Disorder, just because a person has some of the personality traits associated with addiction does not mean they are, or will become, an addict. Practitioners consider specific personality traits to be warning signs, but that’s all they are. There is no personality trait that guarantees an individual will develop an addiction and there is little evidence for an ‘addictive personality’ that is predictive of addiction alone. In short, ‘addictive personality’ is a complete myth.

“The story profiles a middle school student whose obsessive viewing of YouTube content led to extreme behavior changes and eventually, depression and a suicide attempt. The student finds support through therapy at an addiction recovery center…The student in question is a young girl named Olivia who felt at odds with the ‘popular’ kids at her Oakland area school. She began watching YouTube videos after hearing that it was a socially acceptable thing to do… Her viewing habits soon took the place of sleep, which impacted her energy and mood. Her grades began to falter, and external problems within her house – arguments between her parents and the death of her grandmother – led to depression and an admission of wanting to hang herself. Her parents took her to a psychiatric hospital, where she stayed for a week under suicide watch, but her self-harming compulsion continued after her release. She began viewing videos about how to commit suicide, which led to an attempt to overdose on Tylenol” [Note: The name of the woman – Olivia – was a pseudonym].

McClurg interviewed Olivia’s mother for the PBS article and it was reported that Olivia went from being a “bubbly daughter…hanging out with a few close friends after school” to “isolating in her room for hours at a time”. Olivia’s mother also claimed that her daughter had “always been kind of a nerd, a straight. A student who sang in a competitive choir. But she desperately wanted to be popular, and the cool kids talked a lot about their latest YouTube favorites”. According to news reports, all Olivia would do was to watch video after video for hours and hours on end and developed sleeping problems. Over time, the videos being watched focused on fighting girls and other videos featuring violence.

The news story claimed that Olivia was “diagnosed with depression that led to compulsive internet use”. When Olivia went back home she was still feeling suicidal and then spent hours watching YouTube videos on how to commit suicide (and it’s where she got the idea for overdosing on Tylenol tablets).

After a couple of spells in hospital, Olivia’s parents took her to a Californian centre specialising in addiction recovery (called ‘Paradigm’ in San Rafael). The psychologist running the Paradigm clinic (Jeff Nalin) claimed Olivia’s problem was “not uncommon” among clients attending the clinic. Nalin believes (as I do and have pointed out in my own writings) that treating online addictions is not about abstinence but about getting the behaviour under control but developing skills to deal with the problematic behaviour. He was quoted as saying:

“I describe a lot of the kids that we see as having just stuck a cork in the volcano. Underneath there’s this rumbling going on, but it just rumbles and rumbles until it blows. And it blows with the emergence of a depression or it emerges with a suicide attempt…The best analogy is when you have something like an eating disorder. You cannot be clean and sober from food. So, you have to learn the skills to deal with it”.

The story by Gaita asked the question of whether compulsive use of watching YouTube could be called a genuine addiction (and that’s where my views based on my own research were used). I noted that addiction to the internet may be a symptom of another addiction, rather than an addiction unto itself. For instance, people addicted to online gambling are gambling addicts, not internet addicts. An individual addicted to online gaming or online shopping are addicted to gaming or shopping not to the internet.

An individual may be addicted to the activities one can do online and is not unlike saying that an alcoholic is not addicted to a bottle, but to what’s in it. I have gone on record many times saying that I believe anything can be addictive as long there are continuous rewards in place (i.e., constant reinforcement). Therefore, it’s not impossible for someone to become addicted to watching YouTube videos but the number of genuine cases of addiction are likely to be few and far between. Watching video after video is conceptually no different from binge watching specific television series or television addiction itself (topics that I have examined in previous blogs).

I ought to end by saying that some of my own research studies on internet addiction (particularly those co-written with Dr. Attila Szabo and Dr. Halley Pontes and published in the Journal of Behavioral Addictions and Addictive Behaviors Reports – see ‘Further reading’ below) have examined the preferred applications by those addicted to the internet, and that the watching of videos online is one of the activities that has a high association with internet addiction (along with such activities such as social networking and online gaming). Although we never asked participants to specify which channel they watched the videos, it’s fair to assume that many of our participants will have watched them on YouTube), and (as the Camelot lottery advert once said) maybe, just maybe, a few of those participants may have had an addiction to watching YouTube videos.

Despite being a controversial topic, research into a wide variety of online addictions has grown substantially over the last decade. My own research into online addictions has been wide ranging and has included online social networking, online sex addiction, online gaming addiction, online shopping addiction, and online gambling addiction. As early as the late 1990s/early 2000s, I constantly argued that when it came to online addictions, most of those displaying problematic behaviour had addictions on the internet rather than addictions to the internet (i.e., they were not addicted to the medium of the internet but addicted to applications and activities that could be engaged in via the internet).

A recent 2016 paper by Dr. Yifan Wang and colleagues in the journal Frontiers in Public Health described the development of the Questionnaire of Internet Search Dependence (QISD), a tool developed to assess individuals who may be displaying a dependence on using online search engines (such as Google and Baidu). The notion of individuals being addicted to using search engines is not new and was one of five types of internet addiction outlined in a 1999 typology in a paper in the Student British Medical Journal by Dr. Kimberley Young (and what she termed ‘information overload’ and referred to compulsive database searching). Although I criticized the typology on the grounds that most of the types of online addict were not actually internet addicts but were individuals using the medium of the internet to fuel other addictive behaviours (e.g., gambling, gaming, day trading, etc.), I did implicitly acknowledge that activities such as internet database searching could theoretically exist, even if I did not think it was a type of internet addiction.

As far as I am aware, the new scale developed by Wang et al. (2016) is the first to create and psychometrically evaluate an instrument to assess ‘internet search dependence’. As noted by the authors:

“Subsequently, we compiled 16 items to represent psychological characteristics associated with Internet search dependence, based on the literature review and a follow-up interview with 50 randomly selected university students…We adopted the six criteria for behavioral addiction formulated by Griffiths (i.e., salience, mood modification, tolerance, withdrawal, conflict, and relapse) [Griffiths, 1999b]”.

Given the authors claimed they used an early version of my addiction components model (i.e., one from 1999 rather than my most recent 2005 formulation) to help inform item construction, I was obviously interested to see the scale’s formulated items. I have to admit that I had a lot of misgivings about the paper so I wrote a commentary on it that has just been published in the same journal (Frontiers in Public Health). More specifically, I noted in my paper that if an individual was genuinely addicted to searching online databases I would have expected to see all of my six criteria applied as follows:

Salience – This occurs when searching internet databases becomes the single most important activity in the person’s life and dominates their thinking (preoccupations and cognitive distortions), feelings (cravings) and behaviour (deterioration of socialized behaviour). For instance, even if the person is not actually searching the internet they will be constantly thinking about the next time that they will be (i.e., a total preoccupation with internet database searching).

Mood modification – This refers to the subjective experiences that people report as a consequence of internet database searching and can be seen as a coping strategy (i.e., they experience an arousing ‘buzz’ or a ‘high’ or paradoxically a tranquilizing feel of ‘escape’ or ‘numbing’ when searching internet databases).

Tolerance – This is the process whereby increasing amounts of time searching internet databases are required to achieve the former mood modifying effects. This basically means that for someone engaged in internet database searching, they gradually build up the amount of the time they spend searching internet databases every day.

Withdrawal symptoms – These are the unpleasant feeling states and/or physical effects (e.g., the shakes, moodiness, irritability, etc.), that occur when an individual is unable to search internet databases because they are ill, the internet is unavailable, or there is no Wi-Fi on holiday, etc.

Conflict – This refers to the conflicts between the person and those around them (interpersonal conflict), conflicts with other activities (social life, hobbies and interests) or from within the individual themselves (intra-psychic conflict and/or subjective feelings of loss of control) that are concerned with spending too much time searching internet databases.

Relapse – This is the tendency for repeated reversions to earlier patterns of excessive internet database searching to recur and for even the most extreme patterns typical of the height of excessive internet database searching to be quickly restored after periods of control.

Of the 12 QISD items constructed in the new scale, very few appeared to have anything to do with addiction and/or dependence but this is most likely due to the fact that the authors also used data collected from 50 participants to inform their items and not just the criteria in the addiction components model. However, relying heavily on input from their participants resulted in a number of key features in addiction/dependence not even being assessed (i.e., no assessment of salience, mood modification, conflict, relapse or tolerance). A couple of items may peripherally assess withdrawal symptoms (e.g., ‘I will be upset if I cannot find an answer to a complex question through Internet search’) but not in any way that is directly associated with addiction or dependence. This may be because the authors’ conceptualization of ‘dependence’ was more akin to ‘over-reliance’ rather than traditional definitions of dependence.

While the QISD may be psychometrically robust I argued that it appears to have little face validity and does not appear to assess problematic engagement in internet database searching (irrespective of how addiction or dependence is defined). Based on the addiction components model, I concluded my paper by creating my own scale to assess internet search dependence based directly on the addiction components model and which I argued would have much greater face validity than any item currently found in the QISD:

Internet database searching is the most important thing in my life.

Conflicts have arisen between me and my family and/or my partner about the amount of time I spend searching internet databases.

I engage in internet database searching as a way of changing my mood.

Over time I have increased the amount of internet database searching I do in a day.

If I am unable to engage in internet database searching I feel moody and irritable.

If I cut down the amount of internet database searching I do, and then start again, I always end up searching internet databases as often as I did before.

This newly published study is one of the few in the field that has investigated internet addiction from an experimental perspective (as opposed the majority that use self-report survey methods and the increasing number of neuroimaging studies examining what happens inside the brains of those who spend excessive amounts of time online).

Professor Reed’s study involved 100 adult volunteers who were deprived of internet access for four hours. The research team then asked the participants to name a colour (the first one that they could think of) and then gave them 15 minutes to access any websites that they wanted to on the internet. The research team monitored all the sites that the participants visited and after the 15-minute period they were again asked to think of the first colour that came to mind. The participants were also asked to complete various psychometric questionnaires including the Internet Addiction Test (IAT). The IAT is a 20-item test where each item is scored from 0 [not applicable] or 1 [rarely] up to 5 [always]. An example item is “How often do you check your e-mail before something else that you need to do?” Those scoring 80 or above (out of 100) are typically defined as having a probable addiction to the internet by those who have used the IAT in previous studies.

Those classed as “high problem [internet] users” on the basis of IAT scores (and who were deprived internet access) were more likely to choose a colour that was prominent on the websites they visited during the 15-minute period after internet deprivation. This wasn’t found in those not classed as internet addicts. Professor Reed said:

“The internet addicts chose a colour associated with the websites they had just visited [and] suggests that aspects of the websites viewed after a period without the net became positively valued.Similar findings have been seen with people who misuse substances, with previous studies showing that a cue associated with any drug that relieves withdrawal becomes positively valued itself. This is the first time though that such an effect has been seen for a behavioural addiction like problematic internet usage”.

While this is an interesting finding there are some major shortcomings both from a methodological standpoint and from a more conceptual angle. Firstly, the number of high problem internet users that were deprived internet access for four hours comprised just 12 individuals so the sample size was incredibly low. Secondly, the individuals classed as high problem internet users had IAT scores ranging from 40 to 72. In short, it is highly unlikely that any of the participants were actually addicted to the internet. Thirdly, although the IAT is arguably the most used screen in the field, it has questionable reliability and validity and is now very out-dated (having been devised in 1998) and does not use the criteria suggested for Internet Disorder in the latest (fifth) edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Using more recently developed instruments such as our own Internet Disorder Scale would have perhaps overcome some of these problems.

There are also much wider problems with the use of the term ‘internet addiction’ as most studies in the field have really investigated addictions on the internet rather than to the internet. For instance, individuals addicted to online gaming, online gambling or online shopping are not internet addicts. They are gambling addicts, gaming addicts or shopping addicts that are using the medium of the internet to engage in their addictive behaviour. There are of course some activities – such as social networking – that could be argued to be a genuine type of internet addiction as such activities only take place online. However, the addiction is to an application rather than the internet itself and this should be termed social networking addiction rather than internet addiction. In short, the overwhelming majority of so-called internet addicts are no more addicted to the internet than alcoholics are addicted to the bottle.

Over the last few years there has been increasing use of the term ‘digital detox’. According to the Oxford Dictionary, digital detox is “a period of time during which a person refrains from using electronic devices such as smartphones or computers, regarded as an opportunity to reduce stress or focus on social interaction in the physical world”. I have to admit that I often find it hard to switch off from work (mainly because I love my job). Given that my job relies on technology, by implication it also means I find it hard to switch off from technology. Today’s blog is as much for me as anyone reading this and provides some tips on how to cut down on technology use, even if it’s just for the weekend or a holiday. I have compiled these tips from many different online articles as well as some of my own personal strategies.

Digitally detox in increments: For some people, going a few minutes without checking their smartphone or emails is difficult. For many, the urge is reflexive and habitual. If you are one of those people, then ‘baby steps’ are needed. Such individuals need to learn to digitally detox in small increments (i.e., go on a ‘digital diet’). Start by proving to yourself that you can go 15 minutes without technology. Over time, increase the length of time without checking (say) Twitter, Facebook and emails (e.g., 30 minutes, 60 minutes, a couple of hours) until you get into a daily habit of being able to spend a few hours without the need to be online. Another simple trick is to only keep mobile devices partially topped up. This means users have to be sparing when checking their mobile devices.

Set aside daily periods of self-imposed non-screen time: One of the secrets to cutting down technology use to acceptable levels is to keep aside certain times of the day technology-free (meal times and bedtime are a good starting place – in fact, these rooms should be made technology-free). For instance, I rarely look at any emails between 6pm and 8pm as this is reserved for family time (e.g., cooking and eating dinner with the family). Another strategy to try is having a technology-free day at the weekends (e.g., not accessing the internet at all for 24 hours). However, watching television or using an e-reader is fine. Another simple strategy is to have technology-free meal times (at both home and work). Don’t bring your smartphone or tablet to the table.

Only respond to emails and texts at specific times of the day: Only a few individuals are ‘on call’ and have to assume that the message they receive will be an emergency. Looking at emails (say) just three times a day (9am, 1pm, 4pm) will save lots of time in the long run. Turning off email and social media, disabling push notifications, or simply turning the volume setting to silent on electronic devices will also reduce the urge to constantly check mobile devices.

Don’t use your smartphone or tablet as an alarm clock: By using a standard alarm clock to wake you in the morning, you will avoid the temptation to look at emails and texts just as you are about to go to sleep or just wake up (or in the middle of the night if you are a workaholic!).

Engage in out-of-work activities where it is impossible (or frowned upon) to use technology: Nowadays, leisure activities such as going to the pub, having a meal, or going to the cinema, don’t stop people using wireless technology. By engaging in digitally incompatible activities where it is impossible to access technology simultaneously (e.g., jogging, swimming, meditation, outdoor walks in wi-fi free areas) or go to places where technology is frowned upon (e.g., places of worship, yoga classes, etc.) and individual will automatically decrease the amount of screen time. In social situations, you can turn people’s need to check their phones into a game. For instance, in the pub, you could have a game where the first one to check their phone has to buy a round of drinks for everyone else.

Tell your work colleagues and friends you are going on a digital detox: Checking emails and texts can become an almost compulsive behaviour because of what psychologists have termed ‘FOMO’ (fear of missing out) that refers to the anxiety that an interesting or exciting event may be happening elsewhere online. By telling everyone you know that you will not be online for a few hours, they will be less likely to contact you in the first place and you will be less likely check for online messages in the first place. Alternatively, Put your ‘out-of-office’ notification on for a few hours and do something more productive with your time.

Reduce your contact lists: One way to spend less time online is to reduce the number of friends on social networking sites, stop following blogs (but not mine, of course!), delete unused apps, and unsubscribe from online groups that have few benefits. Also, delete game apps that can be time-consuming (e.g., Angry Birds, Candy Crush Saga, etc.).

Get a wristwatch: One of the most common reasons for looking at a smartphone or a tablet is to check the time. If checking the time also leads to individuals noticing they have a text, email or tweet, they will end up reading what has been sent. By using an old fashioned wristwatch (as opposed to new smart watches like the Apple Watch), the urge to reply to messages will decrease.

Think about the benefits of not constantly being online: If you are the kind of person that responds to emails, texts and tweets as they come in, you will write longer responses than if you look at them all in a block. The bottom line is that you can save loads of time to spend on other things if you didn’t spend so long constantly reacting to what is going on in the online world.

Enjoy the silence: Too many people fail to appreciate being in the moment and allowing themselves to resist the urge to log onto their laptops, mobiles and tablets. It is at these times that some people might interpret as boredom that we can contemplate and be mindful. This could be made more formal by introducing meditation into a daily routine. There are also many places that run whole weekends and short breaks where technology is forbidden and much of the time can be spent in quiet contemplation.

Fill the void: To undergo digital detox for any length of time, an individual has to replace the activity with something that is as equally rewarding (whether it is physically, psychologically or spiritually). When I’m on holiday, I catch up on all the novels that I’ve been meaning to read. In shorter spaces of time (such as sitting in boring meetings) I doodle, write ‘to do’ lists, generate ideas to write about, or simply do nothing (and be mindful, aware of the present moment). In short, I try to productive (or unproductive) without having to resort to my technology.

Use technology to beat technology: One thing that can shock technology users is how much time they actually spend on their mobile devices. Working out how much time is actually spent online can be the first step in wanting to cut down. (For instance, someone I once worked with was shocked to find he had spent 72 [24-hour] days in one year playing World of Warcraft). Tech users can download apps that tell them how much time spending online, (e.g., Moment). Being made aware of a problem is often the first step in enabling behavioural change.

Following my recent blogs where I outlined some of the papers that I and my colleagues have published on mindfulness, I got a couple of emails asking if I could do the same thing on other areas that we have been researching into. So, here it is.

Introduction: Recent research has examined the context in which preference for specific online activities arises, leading researchers to suggest that excessive Internet users are engaged in specific activities rather than ‘generalized’ Internet use. The present study aimed to partially replicate and expand these findings by addressing four research questions regarding (i) participants’ preferred online activities, (i) possible expected changes in online behavior in light of hypothetical scenarios, (iii) perceived quality of life when access to Internet was not possible, and (iv) how participants with self-diagnosed Internet addiction relate to intensity and frequency of Internet use. Methods: A cross-sectional design was adopted using convenience and snowball sampling to recruit participants. A total of 1057 Internet users with ages ranging from 16 to 70 years (Mean age= 30 years, SD = 10.84) were recruited online via several English-speaking online forums. Results: Most participants indicated that their preferred activities were (i) accessing general information and news, (ii) social networking, and (iii) using e-mail and/or online chatting. Participants also reported that there would be a significant decrease of their Internet use if access to their preferred activities was restricted. The study also found that 51% of the total sample perceived themselves as being addicted to the Internet, while 14.1% reported that without the Internet their life would be improved. Conclusions: The context in which the Internet is used appears to determine the intensity and the lengths that individuals will go to use this tool. The implications of these findings are further discussed.

Research into Internet addiction (IA) has grown rapidly over the last decade. The topic has generated a great deal of debate, particularly in relation to how IA can be defined conceptually as well as the many methodological limitations. The present review aims to further elaborate and clarify issues that are relevant to IA research in a number of areas including: definition and characterization, incidence and prevalence rates, associated neuronal processes, and implications for treatment, prevention, and patient-specific considerations. It is concluded that there is no consensual definition for IA. Prevalence rates among nationally representative samples across several countries vary greatly (from 1% to 18.7%), most likely reflecting the lack of methodological consistency and conceptual rigor of the studies. The overlaps between IA and other more traditional substance-based addictions and the possible neural substrates implicated in IA are also highlighted. In terms of treatment and prevention, both psychological and pharmacological treatments are examined in light of existing evidence alongside particular aspects inherent to the patient perspective. Based on the evidence analyzed, it is concluded that IA may pose a serious health hazard to a minority of people.

There has been increased research examining the psychometric properties on the Internet Addiction Test (IAT) in different populations. This population-based study examined the psychometric properties and measurement invariance of the IAT in adolescents from three Asian countries. In the Asian Adolescent Risk Behavior Survey (AARBS), 2,535 secondary school students (55.9% girls) aged 12-18 years from Hong Kong (n=844), Japan (n=744), and Malaysia (n=947) completed a survey in 2012-2013 school year. A nested hierarchy of hypotheses concerning the IAT cross-country invariance was tested using multigroup confirmatory factor analyses. Replicating past findings in Hong Kong adolescents, the construct of the IAT is best represented by a second-order three-factor structure in Malaysian and Japanese adolescents. Configural, metric, scalar, and partial strict factorial invariance was established across the three samples. No cross-country differences on Internet addiction were detected at the latent mean level. This study provided empirical support for the IAT as a reliable and factorially stable instrument, and valid to be used across Asian adolescent populations.

Kimberly Young’s initial work on Internet addiction (IA) was pioneering and her early writings on the topic in- spired many others to carry out research in the area. Young’s (2015) recent paper on the ‘evolution of Internet addiction’ featured very little European research, and did not consider the main international evidence that has contributed to our current knowledge about the conceptualization, epidemiology, etiology, and course of Internet-related disorders. This short commentary paper elaborates on important literature omitted by Young that the present authors believe may be of use to researchers. We also address statements made in Young’s (2015) commentary that are incorrect (and therefore misleading) and not systematically substantiated by empirical evidence.

Over the last decade, research on Internet addiction (IA) has increased. However, almost all studies in the area are cross-sectional and do not examine the context in which Internet use takes place. Therefore, a longitudinal study examined the role of conscientiousness (as a personality trait) and classroom hostility (as a contextual factor) in the development of IA. The participants comprised 648 adolescents and were assessed over a 2-year period (while aged 16-18 years). A three-level hierarchical linear model was carried out on the data collected. Findings revealed that (a) lower conscientiousness was associated with IA and this did not change over time and (b) although being in a more hostile classroom did not initially have a significant effect, it increased girls’ IA vulnerability over time and functioned protectively for boys. Results indicated that the contribution of individual and contextual IA factors may differ across genders and over time. More specifically, although the protective effect of conscientiousness appeared to hold, the over-time effect of classroom hostility increased the risk of IA for girls. These findings are discussed in relation to the psychological literature. The study’s limitations and implications are also discussed.

Internet addiction has become an increasingly researched area in many Westernized countries. However, there has been little research in developing countries such as Iran, and when research has been conducted, it has typically utilized small samples. This study investigated the relationship of Internet addiction with stress, depression, anxiety, and loneliness in 1052 Iranian adolescents and young adults. The participants were randomly selected to complete a battery of psychometrically validated instruments including the Internet Addiction Test, Depression Anxiety Stress Scale, and the Loneliness Scale. Structural equation modeling and Pearson correlation coefficients were used to determine the relationship between Internet addiction and psychological impairments (depression, anxiety, stress and loneliness). Pearson correlation, path analysis, multivariate analysis of variance (MANOVA), and t-tests were used to analyze the data. Results showed that Internet addiction is a predictor of stress, depression, anxiety, and loneliness. Findings further indicated that addictive Internet use is gender sensitive and that the risk of Internet addiction is higher in males than in females. The results showed that male Internet addicts differed significantly from females in terms of depression, anxiety, stress, and loneliness. The implications of these results are discussed.

Research into online addictions has grown considerably over the last two decades and much of it has concentrated on problematic gaming, particularly MMORPGs (Massively Multiplayer Online Role-Playing Games). In the latest (fifth) edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013), Internet Gaming Disorder (IGD) (also commonly referred in the literature as problematic gaming and gaming addiction) was included in Section 3 (‘Emerging Measures and Models’) as a promising area that needed future research before being included in the main section of future editions of the DSM.

The DSM-5 proposed nine criteria for IGD (of which five or more need to be endorsed over the period of 12 months and result in clinically significant impairment to be diagnosed as experiencing IGD). More specifically the criteria include (1) preoccupation with games; (2) withdrawal symptoms when gaming is taken away; (3) the need to spend increasing amounts of time engaged in gaming, (4) unsuccessful attempts to control participation in gaming; (5) loss of interest in hobbies and entertainment as a result of, and with the exception of, gaming; (6) continued excessive use of games despite knowledge of psychosocial problems; (7) deception of family members, therapists, or others regarding the amount of gaming; (8) use of gaming to escape or relieve a negative mood; and (9) loss of a significant relationship, job, or educational or career opportunity because of participation in games.

There is no agreement on the prevalence of IGD as the vast majority of studies have surveyed non-representative self-selected samples using over 20 different screening instruments. A review of problematic gaming prevalence studies that I published with Orsi Király, Halley Pontes, and Zsolt Demetrovics (in the 2015 book Mental Health in the Digital Age: Grave Dangers, Great Promise) reported a large variation in the prevalence rates (from 0.2% up to 34%). However, we noted that there were many factors that could have accounted for the wide variation in prevalence rates including the type of gaming examined (i.e., some studies just examined online gaming, whereas others examined console gaming or a mixture of both), sample size, participants’ age range, participant type (i.e., some surveyed the general population while others assessed gamers only), and instruments used to assess gaming.

There have been a handful of studies that have reported the prevalence of IGD using nationally representative samples. The prevalence rates reported were 8.5% of American youth aged 8–18 years, 1.2% of German adolescents aged 13-18 years, 5.5% among Dutch adolescents aged 13-20, and 5.4% among Dutch adults, 4.3% of Hungarian adolescents aged 15-16 years, 1.4% of Norwegian gamers, and 1.6% of European youth from seven countries aged 14-17 years.

There are now over 20 different screening instruments including a number of new ones specifically incorporating the IGD criteria (including a number that I have co-developed with Halley Pontes). The multiplicity of problematic gaming screens remains a key challenge in the field and partially reflects the lack of consensus in terms of the assessment of the phenomenon. A comprehensive 2013 review that I published with Daniel King and others in Clinical Psychology Review examined the criteria of 18 problematic gaming screens. The 18 screens had been utilized in 63 quantitative studies (N=58,415 participants). The main weaknesses identified were (i) inconsistency of core addiction indicators across studies, (ii) a general lack of any temporal dimension, (iii) inconsistent cutoff scores relating to clinical status, (iv) poor and/or inadequate inter-rater reliability and predictive validity, and (v) inconsistent and/or untested dimensionality. We also questioned the appropriateness of certain screens for certain settings, because those used in clinical practice may require a different emphasis than those used in epidemiological, experimental, or neurobiological research settings.

Research into IGD is needed from clinical, epidemiological, and neurobiological aspects of IGD. There has been an increasing number of neurobiological studies on IGD and a 2014 meta-analysis by Dr. Y. Meng and colleagues in Addiction Biology of 10 neuroimaging studies investigating the functional brain response to cognitive tasks from IGD using quantitative effect size signed differential mapping meta-analytic methods. found reliable clusters of abnormal activation in IGD within the regions comprising the bilateral medial frontal gyrus/cingulate gyrus, the left middle temporal gyrus and fusiform gyrus when compared to healthy controls. The same review also found that greater amounts of time spent per week playing was associated with hyper-activity in the left medial frontal gyrus and the right cingulate gyrus. Despite the useful findings reported, one of the major limitations of this meta-analysis was that 90% of the studies reviewed were conducted in Asian countries or regions, which might be problematic since prevalence rates of IGD in these populations are usually inflated compared to prevalence rates reported in Western countries. Furthermore, a systematic review of neuroimaging studies examining Internet addiction (IA) and IGD by Daria Kuss and myself in the journal Brain Sciences concluded that:

“These studies provide compelling evidence for the similarities between different types of addictions, notably substance-related addictions and Internet and gaming addiction, on a variety of levels. On the molecular level, Internet addiction is characterized by an overall reward deficiency that entails decreased dopaminergic activity. On the level of neural circuitry, Internet and gaming addiction lead to neuroadaptation and structural changes that occur as a consequence of prolonged increased activity in brain areas associated with addiction. On a behavioral level, Internet and gaming addicts appear to be constricted with regards to their cognitive functioning in various domains”

Over the last decade, a number of studies have investigated the association between IGD (and its derivatives) and various personality and comorbidity factors. Our recent review in the book Mental Health in the Digital Age: Grave Dangers, Great Promise summarized the research examining the relationship between personality traits and IGD. Empirical studies have shown IGD to be associated with (i) neuroticism, (ii) aggression and hostility, (iii) avoidant and schizoid tendencies, loneliness and introversion, (iv) social inhibition, (v) boredom inclination, (vi) sensation-seeking, (vii) diminished agreeableness, (viii) diminished self-control and narcissistic personality traits, (ix) low self-esteem, (x) state and trait anxiety, and (xi) low emotional intelligence. However, we noted that it was difficult to assess the aetiological significance of such associations because these personality factors are not unique to problematic gaming. Our review also reported that IGD had been associated with various comorbid disorders, including (i) attention deficit hyperactivity disorder, (ii) symptoms of generalized anxiety disorder, panic disorder, depression, and social phobia, and (iii) various psychosomatic symptoms.

According to a 2013 editorial in the journal Addiction, Nancy Petry and Charles O’Brien (2013), IGD will not be included as a separate mental disorder in future editions of the DSM until the (i) defining features of IGD have been identified, (ii) reliability and validity of specific IGD criteria have been obtained cross-culturally, (iii) prevalence rates have been determined in representative epidemiological samples across the world, and (iv) aetiology and associated biological features have been evaluated.

Generally speaking, Internet addiction (IA) has been characterized by excessive or poorly controlled preoccupation, urges, and/or behaviours regarding Internet use that lead to impairment or distress in several life domains. However, according to Dr. Kimberly Young, IA is a problematic behaviour akin to pathological gambling that can be operationally defined as an impulse-control disorder not involving the ingestion of psychoactive intoxicants.

However, I have argued in many of my papers over the last 15 years that the Internet may simply be the means or ‘place’ where the most commonly reported addictive behaviours occur. In short, the Internet may be just a medium to fuel other addictions. Interestingly, new evidence pointing towards the need to make this distinction has been provided from the online gaming field where new studies (including some I have carried out with my Hungarian colleagues) have demonstrated that IA is not the same as other more specific addictive behaviours carried out online (i.e., gaming addiction), further magnifying the meaningfulness to differentiate between what may be called ‘generalized’ and ‘specific’ forms of online addictive behaviours, and also between IA and gaming addiction as these behaviours are conceptually different.

Additionally, the lack of formal diagnostic criteria to assess IA holds another methodological problem since researchers are systematically adopting modified criteria from other addictions to investigate IA. Although IA may share some commonalities with other substance-based addictions, it is unclear to what extent such criteria are useful and suitable to evaluate IA. Notwithstanding the existing difficulties in understanding and comparing IA with behaviours such as pathological gambling, recent research provided useful insights on this topic.

A recent study by Dr. Federico Tonioni (published in a 2014 issue of the journal Addictive Behaviors) involving two clinical (i.e., 31 IA patients and 11 pathological gamblers) and a control group (i.e., 38 healthy individuals) investigated whether IA patients presented different psychological symptoms, temperamental traits, coping strategies, and relational patterns in comparison to pathological gamblers, concluded that Internet-addicts presented higher mental and behavioural disengagement associated with significant more interpersonal impairment. Moreover, temperamental patterns, coping strategies, and social impairments appeared to be different across both disorders. Nonetheless, the similarities between IA and pathological gambling were essentially in terms of psychopathological symptoms such as depression, anxiety, and global functioning. Although, individuals with IA and pathological gambling appear to share similar psychological profiles, previous research has found little overlap between these two populations, therefore, both phenomena are separate disorders.

Despite the fact that initial conceptualizations of IA helped advance the current knowledge and understanding of IA in different aspects and contexts, it has become evident that the field has greatly evolved since then in several ways. As a result of these ongoing changes, behavioural addictions (more specifically Gambling Disorder and Internet Gaming Disorder) have now recently received official recognition in the latest (fifth) edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Moreover, IA can also be characterized as a form of technological addiction, which I have operationally defined as a non-chemical (behavioural) addiction involving excessive human-machine interaction. In this theoretical framework, technological addictions such as IA represent a subset of behavioural addictions featuring six core components: (i) salience, (ii) mood modification, (iii) tolerance, (iv) withdrawal, (v) conflict, and (vi) relapse. The components model of addiction appears to be a more updated framework for understanding IA as a behavioural addiction not only conceptually but also empirically. Moreover, this theoretical framework has recently received empirical support from several studies, further evidencing its suitability and applicability to the understanding of IA.

For many in the IA field, problematic Internet use is considered to be a serious issue – albeit not yet officially recognised as a disorder – and has been described across the literature as being associated with a wide range of co-occurring psychiatric comorbidities alongside an array of dysfunctional behavioural patterns. For instance, IA has been recently associated with low life satisfaction, low academic performance, less motivation to study, poorer physical health, social anxiety, attention deficit/hyperactivity disorder and depression, poorer emotional wellbeing and substance use, higher impulsivity, cognitive distortion, deficient self-regulation, poorer family environment, higher mental distress, loneliness, among other negative psychological, biological, and neuronal aspects.

In a recent systematic literature review conducted by Dr. Wen Li and colleagues (and published in the journal Computers and Human Behavior), the authors reviewed a total of 42 empirical studies that assessed the family correlates of IA in adolescents and young adults. According to the authors, virtually all studies reported greater family dysfunction amongst IA families in comparison to non-IA families. More specifically, individuals with IA exhibited more often (i) greater global dissatisfaction with their families, (ii) less organized, cohesive, and adaptable families, (iii) greater inter-parental and parent-child conflict, and (iv) perceptions of their parents as more punitive, less supportive, warm, and involved. Furthermore, families were significantly more likely to have divorced parents or to be a single parent family.

Another recent systematic literature review conducted by Dr. Lawrence Lam published in the journal Current Psychiatry Reports examined the possible links between IA and sleep problems. After reviewing seven studies (that met strict inclusion criteria), it was concluded that on the whole, IA was associated with sleep problems that encompassed subjective insomnia, short sleep duration, and poor sleep quality. The findings also suggested that participants with insomnia were 1.5 times more likely to be addicted to the Internet in comparison to those without sleep problems. Despite the strong evidence found supporting the links between IA and sleep problems, the author noted that due to the cross-sectional nature of most studies reviewed, the generalizability of the findings was somewhat limited.

IA is a relatively recent phenomenon that clearly warrants further investigation, and empirical studies suggest it needs to be taken seriously by psychologists, psychiatrists, and neuroscientists. Although uncertainties still remain regarding its diagnostic and clinical characterization, it is likely that these extant difficulties will eventually be tackled and the field will evolve to a point where IA may merit full recognition as a behavioural addiction from official medical bodies (ie, American Psychiatric Association) similar to other more established behavioural addictions such as ‘Gambling Disorder’ and ‘Internet Gaming Disorder’. However, in order to achieve official status, researchers will have to adopt a more commonly agreed upon definition as to what IA is, and how it can be conceptualized and operationalized both qualitatively and quantitatively (as well as in clinically diagnostic terms).

Video gaming has evolved from a single-player platform to a multi-player realm where interaction with other players is often a necessity. In order to enter the game, players must first create an avatar, a representation of their self in the game that is used to explore and interact with the virtual environment. When creating an avatar, players can also buy virtual assets to augment and/or enhance their online character. Virtual assets are items or customisations for video game avatars, bases, and characters that are purchased with real money.

In a previous blog, I looked at some of the anecdotal evidence that claimed a few individuals had become ‘addicted’ to buying virtual assets. At the time I wrote that article, there was almost nothing published academically on the psychology of virtual assets and why people bought virtual assets. A few months ago, Jack Cleghorn and I published a qualitative paper in the journal Digital Education Review based on our interviews with gamers that regularly bought virtual assets. Today’s blog looks at some of our findings.

For researchers, the buying of virtual assets provides an opportunity to try and understand why people become so immersed in games and what motivates gamers to spend real money on items that some would consider as having no value. In a multi-player environment, it becomes clear that the avatars seen on screen are graphical representations of someone real and may be part of human desires to be noticed, respected, and interacted with. Furthermore the gamer controlling their avatar has motivations, emotions, thoughts, and feelings. Virtual item purchases are therefore likely to impact on a gamer’s psychological wellbeing.

The growing market for virtual items indicates that transactions are becoming commonplace in gaming. The virtual market functions similarly to real markets in that there is demand, fluctuating markets, and profits to be made. The importance of virtual items to some people is illustrated by a divorce claim in a story on Hyped Talk in which a wife made a claim for over half of her husband’s virtual assets. In a different case (outlined in a 2005 issue of The Lawyer), Qiu Chengwei, a middle-aged man killed a fellow gamer over a dispute involving a virtual item. Obviously these cases are extreme but they highlight the fact that virtual items can have both financial and psychological value for gamers.

But why do people buy virtual items? Performance and general quality of an item is seen to be an important motivation whether the item is real or virtual. Online, an appeal to social status may be a better predictor for purchase behaviour than function. However, some claim that appealing to social status has no motivational significance in purchase behaviour. Another unique element of buying virtual items is the potential exclusivity. Exclusive or limited items tend to be unattainable through gameplay and instead must be bought with money. Exclusivity online has been shown to be of importance, and segmentation is a technique used by the games producers that limits certain items to certain classes, levels, or races. This has been shown to stimulate purchase behaviour. The amount of time invested in a game is also key to understanding spending patterns, and gamers will often buy virtual items after a dedicated amount of gameplay has been spent building an avatar.

Naturally, the longer the amounts of time that are spent online and in-game, the more the player emotionally and psychologically invests in the game. The concept of ‘flow’ (formulated by Mihaly Csikszentmihalyi in many papers and books) has been applied to gaming and can involve becoming emotionally attached to a character (in fact I published a paper on this with Damien Hull and Glenn Williams in a 2013 issue of the Journal of Behavioral Addictions). Flow is the feeling of complete absorption in an activity and affects consciousness and emotions of the individual experiencing it. A key element of feeling ‘flow’ is the experience and perception of the world of the avatar and has been applied to electronic media. The adaptation of ‘flow’ to the virtual world suggests that just like other leisure activities, an individual investing time in an environment where they feel socially accepted can become emotionally attached to their avatar. Gaming has been shown to affect consciousness and emotions of gamers that are both necessary in experiencing ‘flow’. It could be that purchasing of virtual items is also motivated – at least in part – by the feeling of emotional attachment to an avatar.

Gamers are being drawn in to an environment by the appeal of social interaction, manipulation of objects, exploration, and identification with the avatar. To some gamers, the virtual world can takes on more significance than ‘actual’ life and residency in their preferred games is what they consider their actuality. This suggests that the reward of gaming is great, indicating that those individuals who buy virtual items are doing so because they feel involved in an environment that benefits them personally.

Given the lack of empirical research, the qualitative study I published with Jack Cleghorn was based on in-depth interviews with six gamers who all regularly bought in-game virtual assets. We examined the (i) motivations for purchasing virtual items, (ii) psychological impact of purchasing virtual items on self-esteem and confidence, (iii) social benefits of gaming and virtual asset purchasing, (iv) emotional attachment to an avatar, (v) choice of items and customisation of the avatar as a form of self-expression, (v) impulsivity versus thoughtfulness in purchase intentions of virtual items, and (vii) impact of transaction machinery on the ‘game experience’ from a gamer’s perspective.

Using interpretative phenomenological analysis (IPA), the study was exploratory and aimed to understand the psychology underlying purchase intention of virtual items and assets among online gamers. As a result of interviewing the gamers, seven theses emerged: (i) motivation for purchase, (ii) social aspects of the gaming and purchasing, (iii) emotional attachment to the avatar, (iv) psychological reward and impact, (v) self-expression, (vi) ‘stock market gaming’ and gaming culture, and (vii) research/impulse buying. The use of IPA allowed each gamer to share their unique experience of playing and purchase behaviour.

Despite the negative aspects of online gaming, the gamers in our study emphasised a more positive side to buying virtual items and gaming more generally. Item exclusivity and item function were major motivating factors and contributed to an item’s importance in-game. Another key motivation for purchase behaviour was the appeal to social status. Attainment of items demonstrates to others how powerful the gamer is. Naturally, if an item has benefits for the avatar it is more likely that the gamer will spend money to obtain it. Function linked to progression, purchasing items, and buying in-game currency are all sometimes a necessity to progress. Novelty and collectability were also important motivators for some of our gamers. Despite subjective motivations, purchasing virtual items arose out of gaming as a predominant pastime. All of the gamers in our sample were dedicated gamers who spent relatively large amounts of time online and, as perhaps expected, larger gaming commitment to led to purchase behaviour.

An integral part of multiplayer gaming is the interaction with other gamers. The feeling of ‘social presence’ in an online environment is reliant on an emotional response to social interaction and the gamers in our study felt social satisfaction. The game sometimes enabled social interaction that might not otherwise be present. Previous research has shown how emotional attachment to games affects behaviour. Our study highlighted the role of emotional attachment to an avatar as a predictor for purchase intention. As well as emotional attachment increasing likelihood of spending, the spending of real money on items increases the attachment felt. It could be that purchasing virtual items may be a cyclical behaviour. It is also the case that purchasing affects the cognitions and emotions of gamers – ‘pride’ was a feeling that resonated among our interviewed gamers.

Our study also highlighted how gamers research items before purchasing them. It might be expected that easy-to-use transaction machinery might facilitate spending. However, in reality, the gamers we interviewed were guarded with their spending online and recommendations from friends playing a major role in purchase behaviour. Virtual assets can be then researched and the placing of real monetary value on the virtual items indicates the value they may hold to the gamer. Unlike media coverage focussing on the more negative impact of online gaming, our study highlighted the positive aspects of purchasing virtual assets for the gamer. They are able to feel connected socially, feel confidence in themselves and their success, express their inner and ideal self without constraint or fear, build lasting relationships, impress people, and generally benefit from gaming and buying virtual items.

Over the last 15 years, research into various online addictions has greatly increased. Alongside this, there have been scholarly debates about whether internet addiction really exists. Some may argue that because internet use does not involve the ingestion of a psychoactive substance, then it should not be considered a genuine addictive behaviour. However, the latest (fifth) edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) re-classified ‘Gambling Disorder’ as a behavioural addiction rather than as a disorder of impulse control. The implications of this reclassification are potentially far-reaching. The most significant implication is that if an activity that does not involve the consumption of drugs (i.e., gambling) can be a genuine addiction accepted by the psychiatric and medical community, there is no theoretical reason why other problematic and habitual behaviours (e.g., shopping, work, exercise, sex, video gaming, etc.) cannot be classed as a bone fide addiction.

There have also been debates among scholars that consider excessive problematic internet use to be a genuine addiction as to whether the those in the field should study generalized internet addiction (the totality of all online activities) and/or specific addictions on the internet such as internet gambling, internet gaming and internet sex. Since the late 1990s, I have constantly argued that there is a fundamental difference between addictions on the internet, and addictions to the internet. I argued that the overwhelming majority of individuals that were allegedly addicted to the internet were not internet addicts but were individuals that used the medium of the internet as a vehicle for other addictions. More specifically, I argued that internet gambling addicts and internet gaming addicts were not internet addicts but were gambling and gaming addicts using the convenience and ubiquity of the internet to gamble or play video games.

Prior to the publication of the latest DSM-5, there had also been debates as to whether ‘internet addiction’ should be introduced into the text as a separate disorder. Following these debates, the Substance Use Disorder Work Group (SUDWG) recommended that the DSM-5 include a sub-type of problematic internet use (i.e., internet gaming disorder [IGD]) in Section 3 (‘Emerging Measures and Models’) as an area that needed future research before being included in future editions of the DSM. However, far from clarifying the debates surrounding generalized versus specific internet use disorders, the section of the DSM-5 discussing IGD noted that:

“There are no well-researched subtypes for Internet gaming disorder to date. Internet gaming disorder most often involves specific Internet games, but it could involve non-Internet computerized games as well, although these have been less researched. It is likely that preferred games will vary over time as new games are developed and popularized, and it is unclear if behaviors and consequence associated with Internet gaming disorder vary by game type…Internet gaming disorder has significant public health importance, and additional research may eventually lead to evidence that Internet gaming disorder (also commonly referred to as Internet use disorder, Internet addiction, or gaming addiction) has merit as an independent disorder” (p.796).

In light of what has been already highlighted in previous research, two immediate problematic issues arise from these assertions. Firstly, IGD is clearly seen as synonymous with internet addiction as the text claims that internet addiction and internet use disorder are simply other names for IGD. Secondly – and somewhat confusingly – it is asserted that IGD (which is by definition internet-based) can also include offline gaming disorders.

With regards to the first assertion, internet addiction and online gaming addiction are not the same. A number of recent studies (including ones I’ve co-authored) clearly shows that to be the case. The second assertion that IGD can include offline video gaming is both baffling and confusing. Some researchers consider video games as the starting point for examining the characteristics of gaming disorder, while others consider the internet as the main platform that unites different addictive internet activities, including online games. For instance, I have argued that although all addictions have particular and idiosyncratic characteristics, they share more commonalities than differences (i.e., salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse), and likely reflects a common etiology of addictive behaviour. For me, IGD is clearly a sub-type of video game addiction. For people like Dr. Kimberley Young, ‘cyber-relationship addictions’, ‘cyber-sexual addictions’, ‘net compulsions’ (gambling, day trading) and ‘information overload’ are all internet addictions. However, many would argue that these – if they are addictions – are addictions on the internet, not to it. The internet is a medium and it is a situational characteristic. The fact that the medium might enhance addictiveness or problematic behaviour does not necessarily make it a sub-type of internet addiction.

However, recent studies have made an effort to integrate both approaches. For instance, some researchers claim that neither the first nor the second approach adequately captures the unique features of Massively Multiplayer Online Role-Playing Games (MMORPGs), and argue an integrated approach is a necessity. A common observation is that “Internet users are no more addicted to the Internet than alcoholics are addicted to bottles”. The internet is just a channel through which individuals may access whatever content they want (e.g., gambling, shopping, chatting, sex). On the other hand, online games differ from traditional standalone games, such as offline video games, in important aspects such as the social dimension or the role-playing dimension that allow interaction with other real players. Consequently, it could be argued that IGD can either be viewed as a specific type of video game addiction, or as a variant of internet addiction, or as an independent diagnosis. However, the idea that IGD can include offline gaming disorders does little for clarity or conceptualization.

Finally, it is also worth mentioning that there are some problematic online behaviours that could be called internet addictions as they can only take place online. The most obvious activity that fulfills this criterion is social networking as it is a ‘pure’ online activity and does not and cannot take place offline. Other activities such as gambling, gaming, and shopping can still be engaged in offline (as gamblers can go to a gambling venue, gamers can play a standalone console game, shoppers can go to a retail outlet). However, those engaged in social networking would not (if unable to access the internet) walk into a big room of people and start chatting to them all. However, even if social networking addiction is a genuine internet addiction, social networking itself is still a specific online application and could still be considered an addiction on the internet, rather than to it.

Based on recent empirical evidence, IGD (or any of the alternate names used to describe problematic gaming) is not the same as Internet Addiction Disorder. The gaming studies field needs conceptual clarity but as demonstrated, the DSM-5 itself is both misleading and misguided when it comes to the issue of IGD.